Extraction of pitch in adverse conditions

The paper proposes a method for the extraction of pitch in adverse conditions. The real environment, in which degradation is due to several unpredictable sources, like additive noise, reverberation and channel noise, is treated as an adverse condition. The proposed method is based on knowledge of glottal closure (GC) events. A GC event is the instant at which closure of vocal folds takes place within a pitch period. The Hilbert envelope of the linear prediction (LP) residual gives information about the location of GC events. Autocorrelation analysis is performed on the Hilbert envelope of the LP residual. The properties of the Hilbert envelope of the LP residual are exploited for the extraction of pitch from the autocorrelation sequence. The results of the proposed method are compared with the simple inverse filtering technique (SIFT) algorithm. The performance of the proposed algorithm is found to be superior, even in adverse conditions.